Increasing density of data transmitted or stored reduces the cost of transmitting and storing the data and the time it takes to transmit and store data. Therefore, it has been a long term goal of the electronics industry to increase the density of data transmitted or stored. Many systems use run-length limited (RLL) coding and peak detection (PD) to achieve high reliability and high densities. A further increase in density can be achieved using more advanced techniques such as partial response (PR) signaling and maximum-likelihood (ML) sequence detectors such as Viterbi detectors, or a combination of the two.
Partial response (PR) signaling is a technique that enforces spectral properties and allows a controlled amount of intersymbol interference. ML sequence estimation, and particularly the Viterbi algorithm, improves the detection of symbol sequences in the presence of intersymbol interference. ML sequence estimation allows most PR schemes to perform practically in a system with errors caused by intersymbol interference.
PR signaling also allows a better handling of intersymbol interference and a more efficient utilization of the bandwidth of a given channel. Because the intersymbol interference is known to be present, the receiver can take it into account. PR signaling in communications allows transmissions at the Nyquist rate, and provides a favorable trade-off between error probability and the available spectrum. The PR systems described by the polynomials 1+D, 1−D, and 1−D2 are called duobinary, dicode, and class-IV, respectively, where D represents one bit cell delay and D2 represents 2 bit cell delays. D=e−jωt, where ω is a frequency variable in radians per second and t is the sampling time interval in seconds. The PR4 magnitude response, 1−D2, emphasizes midband frequencies and results in a read channel with increased immunity to noise and distortion at both low and high frequencies.
Conventional disc drives are used to record and to retrieve information. As discs become more prevalent as the medium of choice for storing information in both computer and home entertainment equipment, disc drives likewise become more prevalent and important components of such electronic systems. PR and ML have been employed in communications signaling for many years, and have now been applied commercially within magnetic hard disk drives. PR4 is presently a preferred partial response system in disc drives, since there is a close correlation between the idealized PR4 spectrum, and the natural characteristics of a magnetic data write/read channel. Application of the Viterbi algorithm to PR4 data streams within a magnetic recording channel is known to improve detection of original symbol sequences in the presence of intersymbol interference and also to improve signal to noise ratio over comparable peak detection techniques.
EPR4 and EEPR4 are higher order PR detection schemes that further increase the density of data that can be stored and transmitted.
FIG. 1 shows a portion of a conventional detector 10, the detector 10 can be a PR4, EPR4, or an EEPR4 detector. The detector 10 has a slicer 20 that samples a data stream to obtain data samples x′(T).
The output of the slicer 20 is also connected to a phase error estimator 22, typically through an equalizer (not shown). The phase error estimator 22 is coupled to a D to A converter 24 whose output is provided to an oscillator 26, which generates the clock, clk(T), that clocks the slicer 20 to control the data sample rate. Each data sample x′(T) is passed to the phase error estimator 22 that determines the timing error for the sample x′(T) and outputs a signal that adjusts the clock frequency of the oscillator 26.
The output of the slicer 20 is also connected to a Viterbi detector. The slicer 20 outputs a sequence of data samples, which are input to the Viterbi detector 28 for analysis and detection to aid in obtaining the decoded data. The output of the Viterbi detector 28 provides the data stream to the system for further detection and analysis.
A problem with PR detectors 10 is that as the density increases or as the complexity of the detector increases the same amount of noise that was previously acceptable can cause false detection of the sample. A false detection can lead to a timing error that will cause the oscillator to adjust the clock frequency to an incorrect frequency. Clocking the slicer 20 at a frequency that does not match the data rate will cause the slicer 20 to sample the next data sample at the wrong time, which will lead to an incorrect data value and to an incorrect timing error for the next data sample, leading to the data value after that being sampled at the wrong time, and so on.